I recently spoke to one of our customers about how they could better leverage the knowledge, skills and capabilities of each of their many and highly-skilled employees, and in return be able to execute projects faster and achieve better results. Our customer's business is complex, and their organizational structure so fluid that no manager can keep up with the skills and capabilities of each employee. As a result there can be value in optimizing the way employees are deployed and assigned to projects.
As with any large organization, the one in question often sets in motion new cross-organizational initiatives to support one or several strategic objectives. For such initiatives to be successful it is crucial to put together a high performance team that posses the required experience and capabilities.
How can analytics help?
What if we consolidated the relevant skills, preferences and behaviours of all employees in an enterprise-wide human capital database and used analytics to determine how to utilize them in the most efficient way?
Who says that, for example, the head of corporate business development is the best person to decide which ten employees are the right ones to head a project focused on introducing the company's products to a new market such as Indonesia?
The future of setting the right team
Imagine that you are the manager in charge of the above strategic initiative. Your business plan has been approved and you have been given a budget and time frame for when the new office is supposed to be set up. All you need is the right team.
You request the ten best matching employees from the company's human capital database, which contains information about each of the organization’s 25,000 employees.
You enter the project's start and end date, Indonesia as the main location where work is to be carried out, total budget, and select the required skills, such as understanding of Indonesian culture etc.
The system returns the ten best matching employees. You notice how each employee has been given a score between 0 and 100% depending on how well they meet the requirements.
When looking closer at the employees' profiles you learn that several of them have worked together in the past, two of them were born in Indonesia and speak the local language, they all live close to an airport with direct flights to Jakarta, and three of them have experience with launching products in a new market.
After going through each employees profile you feel satisfied that you have identified a good team but there is a small problem. One of the employee's score is only 70% fit for the job due to the fact that he cannot participate from day one. It seems he is locked up in another project during the first two weeks.
You click "find similar profile" and the system returns a match that is free during the entire project period. The bad news is that she is only 73% fit for the job as she lacks the necessary understanding of Asian culture; however, according to the system she will be 81% fit if she participates in a short cultural training course. You check the new candidate's upcoming schedule and note that she is free to take the course prior to heading to Jakarta with the rest of the team.
With an average matching score of 90.4% you are confident that you are sending the right team to Indonesia.
Analytics adds increasing value to many areas of the organization, and human capital optimisation is just one of them. This scenario gives you a taste of where an organisation can optimise to achieve better business outcomes. How can analytics help you build your business?